On Singularities and Black Holes in Combination-Driven Models of Technological Innovation Networks

PLoS One. 2016 Jan 28;11(1):e0146180. doi: 10.1371/journal.pone.0146180. eCollection 2016.

Abstract

It has been suggested that innovations occur mainly by combination: the more inventions accumulate, the higher the probability that new inventions are obtained from previous designs. Additionally, it has been conjectured that the combinatorial nature of innovations naturally leads to a singularity: at some finite time, the number of innovations should diverge. Although these ideas are certainly appealing, no general models have been yet developed to test the conditions under which combinatorial technology should become explosive. Here we present a generalised model of technological evolution that takes into account two major properties: the number of previous technologies needed to create a novel one and how rapidly technology ages. Two different models of combinatorial growth are considered, involving different forms of ageing. When long-range memory is used and thus old inventions are available for novel innovations, singularities can emerge under some conditions with two phases separated by a critical boundary. If the ageing has a characteristic time scale, it is shown that no singularities will be observed. Instead, a "black hole" of old innovations appears and expands in time, making the rate of invention creation slow down into a linear regime.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Algorithms
  • Culture
  • Diffusion of Innovation
  • Humans
  • Inventions / statistics & numerical data*
  • Inventions / trends
  • Models, Statistical

Grants and funding

This work was supported by the Fundacion Botin and by the Spanish Ministry of Economy and Competitiveness, Grant FIS2013-44674-P and FEDER and by the Santa Fe Institute, where most of this work was done. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.